Translating "Big Data" in Oncology for Clinical Benefit: Progress or Paralysis.
Anna D BarkerJerry S H LeePublished in: Cancer research (2022)
The molecular characterization of cancer through genomics, data from multiomics technologies, molecular-driven clinical trials, and internet-enabled devices capturing patient context and real-world data are creating an unprecedented big data revolution across the cancer research-care continuum. While big data has translated to benefit for some patients, it has also created new problems. Our intent in this brief communication is to explore some examples of progress and key challenges that remain. The problems are not intractable, but success will require rethinking and rebuilding an information and evidence-based learning system that moves beyond paralysis to shape a better future for patients with cancer.
Keyphrases
- big data
- artificial intelligence
- machine learning
- papillary thyroid
- clinical trial
- mental health
- end stage renal disease
- palliative care
- squamous cell
- newly diagnosed
- chronic kidney disease
- prognostic factors
- health information
- peritoneal dialysis
- lymph node metastasis
- randomized controlled trial
- case report
- squamous cell carcinoma
- quality improvement
- single cell
- current status
- patient reported
- study protocol
- social media
- affordable care act